Brain age prediction in stroke patients: Highly reliable but limited sensitivity to cognitive performance and response to cognitive training

Richard, Geneviève; Kolskår, Knut-Kristian; Ulrichsen, Kristine M.; Kaufmann, Tobias; Alnæs, Dag; Sanders, Anne-Marthe; Dørum, Erlend S.; Sánchez, Jennifer Monereo; Petersen, Anders; Ihle‐Hansen, Hege; Nordvik, Jan Egil

doi:10.1016/j.nicl.2019.102159

Cited by 45 publications

(52 citation statements)

References 40 publications

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“…The protocol have previously been described in detail (Richard et al, 2020). Briefly, after inclusion the participants completed MRI assessment at three timepoints: timepoint 1, at timepoint 2 on average 3-4 weeks after timepoint 1 without additional contact to enable a double baseline for comparison, and at timepoint 3, after the participant completed the training protocol.…”

Section: Study Protocolmentioning

confidence: 99%

“…The patients performed a computerized working memory training program (Cogmed QM, Cogmed Systems AB, Stockholm, Sweden), comprising 12 auditory-verbal and visual-spatial working memory tasks. The implementation of the protocol has previously been reported in detail (Richard et al, 2020). Briefly, the training comprised five weekly training sessions over 3-4 weeks, with 17 training sessions for each participant in total.…”

Section: Cognitive Trainingmentioning

confidence: 99%

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Reliability, sensitivity and predictive value of fMRI during multiple object tracking as a marker of cognitive training gain in combination with tDCS in stroke survivors

Kolskår

Richard

Alnæs

et al. 2019

Preprint

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Computerized cognitive training (CCT) combined with transcranial direct current stimulation (tDCS) has showed some promise in alleviating cognitive impairments in patients with brain disorders, but the robustness and possible mechanisms are unclear. In this prospective doubleblind randomized clinical trial, we investigated the feasibility and effectiveness of combining CCT and tDCS, and tested the predictive value of and training-related changes in fMRI-based brain activation during attentive performance (multiple object tracking) obtained before, during and after the three-weeks intervention. Patients were randomized to one of two groups, receiving CCT and either (1) tDCS targeting left dorsolateral prefrontal cortex (1 mA), or (2) sham tDCS, with 40s active stimulation (1 mA) before fade out of the current. 77 patients were enrolled in the study, 54 completed the cognitive training, and 48 completed all training and MRI sessions. We found significant improvement in performance across all trained tasks, but no additional gain of tDCS. fMRI-based brain activation showed high reliability, and higher cognitive performance was associated with increased tracking-related activation in the dorsal attention network and DMN as well as anterior cingulate after compared to before the intervention. We found no significant associations between cognitive gain and brain activation measured before training or in the difference in activation after intervention.Combined, these results show significant training effects on cognitive tasks in stroke survivors, with no clear evidence of additional gain of concurrent tDCS.

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Section: Study Protocolmentioning

confidence: 99%

Section: Cognitive Trainingmentioning

confidence: 99%

Reliability, sensitivity and predictive value of fMRI during multiple object tracking as a marker of cognitive training gain in combination with tDCS in stroke survivors

Kolskår

Richard

Alnæs

et al. 2019

Preprint

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“…Individual variation in delta estimations are associated with a range of cognitive and biological measures [10,11,12,13,14,15,16,17], including cardiovascular health [14], and differences in brain age have been established between patient groups and healthy controls: individuals with conditions such as Alzheimer's disease, multiple sclerosis, epilepsy, and psychiatric disorders show on average older brain age relative to their chronological age [9,18,19,20,21,22]. Longitudinal studies have documented highly reliable brain age prediction in stroke patients [23], and accelerated brain aging in patients with schizophrenia and multiple sclerosis [21,24,25].…”

Section: Introductionmentioning

confidence: 99%

Multimodal brain-age prediction and cardiovascular risk: The Whitehall II MRI sub-study

Lange

Anatürk

Kaufmann

et al. 2020

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Brain age is becoming a widely applied imaging-based biomarker of neural aging and potential proxy for brain integrity and health. We estimated multimodal and modality-specific brain age in the Whitehall II MRI cohort using machine learning and imaging-derived measures of gray matter morphology, diffusion-based white matter microstructure, and resting state functional connectivity. Ten-fold cross validation yielded multimodal and modality-specific brain age estimates for each participant, and additional predictions based on a separate training sample was included for comparison. The results showed equivalent age prediction accuracy between the multimodal model and the gray and white matter models (R 2 of 0.34, 0.31, and 0.31, respectively), while the functional connectivity model showed a lower prediction accuracy (R 2 of 0.01). Cardiovascular risk factors, including high blood pressure, alcohol intake, and stroke risk score, were each associated with more apparent brain aging, with consistent associations across modalities.

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“… b One patient had intracerebral hemorrhage. ( Kolskår et al., 2020 ; Richard et al, 2020 ; Ulrichsen et al, 2020 ). c Chi square statistics.…”

Section: Methodsmentioning

confidence: 99%

“…To test these hypotheses, we obtained data using a whole-report behavioral paradigm from chronic stroke patients who were invited to take part of a randomized, double blind study aimed to test the utility of tDCS in combination with CCT to improve cognitive performance following stroke ( Kolskår et al, 2020 ; Richard et al, 2020 ; Ulrichsen et al, 2020 ). We used cross-sectional data from 70 chronic stroke patients collected during the first assessment and 140 matched controls, as well as longitudinal data (6 sessions) from 54 chronic stroke patients who completed the full study protocol.…”

Section: Introductionmentioning

confidence: 99%

TVA-based modeling of short-term memory capacity, speed of processing and perceptual threshold in chronic stroke patients undergoing cognitive training: case-control differences, reliability, and associations with cognitive performance

Richard

Petersen

Ulrichsen

et al. 2020

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Attentional deficits following stroke are common and pervasive, and are important predictors for functional recovery. Attentional functions comprise a set of specific cognitive processes allowing to attend, filter and select among a continuous stream of stimuli. These mechanisms are fundamental for more complex cognitive functions such as learning, planning and cognitive control, all crucial for daily functioning. The distributed functional neuroanatomy of these processes is a likely explanation for the high prevalence of attentional impairments following stroke, and underscores the importance of a clinical implementation of computational approaches allowing for sensitive and specific modeling of attentional sub-processes. The Theory of Visual Attention (TVA) offers a theoretical, computational, neuronal and practical framework to assess the efficiency of visual selection performance and parallel processing of multiple objects. Here, in order to assess the sensitivity and reliability of TVA parameters reflecting short-term memory capacity (K), processing speed (C) and perceptual threshold (t0), we used a whole-report paradigm in a cross-sectional case-control comparison and across six repeated assessments over the course of a three-week computerized cognitive training (CCT) intervention in chronic stroke patients (> 6 months since hospital admission, NIHSS ≤ 7 at hospital discharge). Cross-sectional group comparisons documented lower short-term memory capacity, lower processing speed and higher perceptual threshold in patients (n = 70) compared to age-matched healthy controls (n = 140). Further, longitudinal analyses in stroke patients during the course of CCT (n = 54) revealed high reliability of the TVA parameters, and higher processing speed at baseline was associated with larger cognitive improvement after the intervention. The results support the feasibility, reliability and sensitivity of TVA-based assessment of attentional functions in chronic stroke patients.

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Brain age prediction in stroke patients: Highly reliable but limited sensitivity to cognitive performance and response to cognitive training

Cited by 45 publications

References 40 publications

Reliability, sensitivity and predictive value of fMRI during multiple object tracking as a marker of cognitive training gain in combination with tDCS in stroke survivors

Reliability, sensitivity and predictive value of fMRI during multiple object tracking as a marker of cognitive training gain in combination with tDCS in stroke survivors

Multimodal brain-age prediction and cardiovascular risk: The Whitehall II MRI sub-study

TVA-based modeling of short-term memory capacity, speed of processing and perceptual threshold in chronic stroke patients undergoing cognitive training: case-control differences, reliability, and associations with cognitive performance

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